Target motion video tracking method based on Python environment

Abstract

The invention discloses a target motion video tracking method based on a Python environment, which belongs to the field of target tracking, and comprises the following steps: step 1, a system downloads historical videos in monitoring video equipment and performs framing on the historical videos to obtain corresponding pictures; 2, preprocessing each frame of picture to obtain a training set and atest set; 3, training a neural network model in a Python environment, and obtaining a required target in the video by using the trained data; 4, calculating coordinates of a target center point, and tracking the target in real time; 5, detecting a motion direction parameter and a time parameter of the target according to the target center point; and step 6, the system automatically draws a motiontrail diagram and a displacement diagram of the target according to the direction and time parameters so as to provide visual data. According to the invention, based on the Python environment, the target to be identified is trained by using the deep convolution model, and targeted model training can be carried out, so that the recognition precision and recognition speed of the tracking system forthe target are improved, and the detection and tracking in the farm environment are ensured.

Description

technical field [0001] The invention relates to the field of target tracking, in particular to a moving target tracking method implemented in a Python environment. Background technique [0002] With the advent of the Internet era, the rapidly developing video surveillance system has been widely used in various fields, especially in traffic safety, community security, bank monitoring, industrial inspection, medical imaging analysis and other aspects. It can be said that video Surveillance systems have penetrated into every aspect of our lives and are already an essential part. Although the application of the video system is so wide and the technology is relatively mature, it still has greater prospects. As far as it is concerned, its application in the field of animal husbandry is not so common, and the technology is relatively not so mature. The main reason is It is still because the cost of environmental installation and technical support in the early stage is relatively h...

AI Technical Summary

Problems solved by technology

At present, regardless of whether it is a private farm or not, there are varying degrees of low automation, and most of them still detect the state of animals manually, which requires high working hours and professionalism of workers.

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